public class VECM
extends java.lang.Object
implements java.io.Serializable
A vector error correction model (VECM(p)) has one the following specifications:
(Transitory):
ΔY_t = μ + Π * Y_{t-1} + Σ[Γ_i * Y_{t-i}] + ψ * D_t + ε_t, (i = 1, 2, ..., p-1),
or
(Long-run):
ΔY_t = μ + Π * Y_{t-p} + Σ[Γ_i * Y_{t-i}] + ψ * D_t + ε_t, (i = 1, 2, ..., p-1),
where Y_s, μ and ε_s are n-dimensional vectors;
the impact matrix Π and the coefficients {Γ_i} of the lagged time series are (n * n) matrices;
D_t is an (m * 1) vector which contains all exogenous variables at time t (excl. the intercept term),
and its coefficients are represented by a (n * m) matrix ψ.| Constructor and Description |
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VECM(VECM that)
Copy constructor.
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VECM(Vector mu,
Matrix pi,
Matrix[] gamma,
Matrix psi,
Matrix sigma)
Construct a VECM(p) model.
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| Modifier and Type | Method and Description |
|---|---|
int |
dimension()
Get the dimension of multivariate time series.
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ImmutableMatrix |
gamma(int i)
Get the AR coefficient on the i-th lagged differences.
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ImmutableVector |
mu()
Get the intercept vector.
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int |
p()
Get the order of the VECM model.
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ImmutableMatrix |
pi()
Get the impact matrix.
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ImmutableMatrix |
psi()
Get the coefficients of the deterministic terms.
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ImmutableMatrix |
sigma()
Get the covariance matrix of white noise.
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public VECM(Vector mu, Matrix pi, Matrix[] gamma, Matrix psi, Matrix sigma)
mu - the intercept (constant) vectorpi - the impact matrixgamma - the AR coefficients on the lagged differences; null if p = 1psi - the coefficients of the deterministic terms (excluding the intercept term)sigma - the covariance matrix of white noisepublic VECM(VECM that)
that - a VECM modelpublic ImmutableVector mu()
public ImmutableMatrix pi()
public ImmutableMatrix gamma(int i)
i - an index, count from 1public ImmutableMatrix psi()
nullpublic ImmutableMatrix sigma()
public int dimension()
public int p()